The field of machine learning constitutes a modern approach to artificial intelligence. It is situated in between computer science, neuroscience, statistics, and robotics, with applications ranging all over science and engineering, medicine, economics, etc. Machine learning algorithms automate the process of learning, thus allowing prediction and decision making machines to improve with experience.
This lecture will cover a contemporary spectrum of supervised learning methods. All lecture material will be in English.
The course will use the inverted classroom concept. Students work through the relevant lecture material at home. The material is then consolidated in a 4 hours/week practical session.
- Course type
- 6 CP
- Summer Term 2019
every week on Thursday from 10:00 to 14:00 in room IA 0/158-79 (PC-Pool 1).
First appointment is on 04.04.2019
Last appointment is on 11.07.2019
The course requires basic mathematical tools from linear algebra, calculus, and probability theory. More advanced mathematical material will be introduced as needed. The practical sessions involve programming exercises in Python. Participants need basic programming experience. They are expected to bring their own devices (laptops).
Most of the lecture is based on the following video lectures: https://www.youtube.com/playlist?list=PLD63A284B7615313A (CC license). All material will be made available in a moodle course.